London's Population Over Time

For trend prediction London's population

By Eva Murray [source]

About this dataset

This file contains data on the projected population of London from 2011 to 2050. The data comes from the London Datastore and offers a glimpse into the future of one of the world's most populous cities

How to use the dataset

Research Ideas

• Predicting crime rates based on population growth
• Determining which areas of London will need more infrastructure to accommodate the growing population
• Planning for different marketing and advertising strategies based on demographics

Acknowledgements

Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: central_trend_2017_base.csv | Column name | Description | |:--------------|:------------------------------------| | gss_code | The GSS code for the area. (String) | | district | The name of the district. (String) | | component | The population component. (String) | | sex | The sex of the population. (String) | | age | The age of the population. (String) | | 2011 | The population in 2011. (Integer) | | 2012 | The population in 2012. (Integer) | | 2013 | The population in 2013. (Integer) | | 2014 | The population in 2014. (Integer) | | 2015 | The population in 2015. (Integer) | | 2016 | The population in 2016. (Integer) | | 2017 | The population in 2017. (Integer) | | 2018 | The population in 2018. (Integer) | | 2019 | The population in 2019. (Integer) | | 2020 | The population in 2020. (Integer) | | 2021 | The population in 2021. (Integer) | | 2022 | The population in 2022. (Integer) | | 2023 | The population in 2023. (Integer) | | 2024 | The population in 2024. (Integer) | | 2025 | The population in 2025. (Integer) | | 2026 | The population in 2026. (Integer) | | 2027 | The population in 2027. (Integer) | | 2028 | The population in 2028. (Integer) | | 2029 | The population in 2029. (Integer) | | 2030 | The population in 2030. (Integer) | | 2031 | The population in 2031. (Integer) | | 2032 | The population in 2032. (Integer) | | 2033 | The population in 2033. (Integer) | | 2034 | The population in 2034. (Integer) | | 2035 | The population in 2035. (Integer) | | 2036 | The population in 2036. (Integer) | | 2037 | The population in 2037. (Integer) | | 2038 | The population in 2038. (Integer) | | 2039 | The population in 20 |

Acknowledgements

If you use this dataset in your research, please credit Eva Murray.

About this dataset

Context

The dataset tabulates the London population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of London across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of London was 10,442, a 0.53% increase year-by-year from 2021. Previously, in 2021, London population was 10,387, an increase of 1.18% compared to a population of 10,266 in 2020. Over the last 20 plus years, between 2000 and 2022, population of London increased by 1,711. In this period, the peak population was 10,442 in the year 2022. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the London is shown in this column.
• Year on Year Change: This column displays the change in London population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for London Population by Year. You can refer the same here

Introduction

The 2023 mid-year estimate (MYE) is the current official estimate of the population for local authorities in England and Wales. Estimates are produced annually by the Office for National Statistics (ONS) and the 2023 MYE was published on 15 July 2024.

Comparison to previous MYE data

The previous MYE series (for the period 2012-2020) starts with the 2011 census estimate. Each subsequent year’s population is calculated by adding estimates of births, deaths and migration to the previous year’s population. The 2021 MYE represents a break in this series as it uses the 2021 census as its base.

The ONS revised the 2012-2020 MYE series to bring it in line with the 2021 MYE, so that comparisons could be made between between this series and the previous series. The values plotted on the chart are the revised values of the previously published estimates for 2011 to 2022, together with the estimates for 2023.

Key Points

• London’s mid-2023 population was 8.945 million
• London’s population increased by 76,300 persons compared to the previous mid-year value
• Components of change were as follows:
• 105,100 births and 53,500 deaths (natural change of 51,600)
• Net domestic migration was an outflow of 129,200
• Net international migration was an inflow of 154,100

Population Change

London’s 2023 population was 8,945,310. The first chart below shows the 2023 MYE in the context of previous estimates. There is an uptick after a temporary decrease in population which we attribute to the COVID-19 pandemic.

https://cdn.datapress.cloud/london/img/dataset/763802e7-af17-4b77-995d-44c494fb68af/2025-06-09T20%3A56%3A29/666cd938678c5361c953cb608e532416.webp" width="1152" alt="Embedded Image" />

Components of Change

Births, deaths and migration form the components of population change.

The 2023 MYE value for births was 4% lower than that in 2022, and for deaths 3% higher. The consequent value for natural change (births - deaths) was 10% lower than in 2022.

At -129,000, the value for domestic migration (migration within the UK) was nearly 3% higher than the 2022 value, so still significantly lower than the peak net outflow during the COVID-19 pandemic of -186,000. An outflow of domestic migrants from London is normal and this has been the case each year for the last two decades. This flow is partly because many international in-migrants initially settle in London before moving out to other parts of the UK. The second move in this sequence is counted as a domestic migration.

There has been a marked change in immigration since 2021. This can be attributed to the end of free movement for EU nationals, easing of travel restrictions following the COVID 19 pandemic, and the war in Ukraine. At over 150,000, the 2023 MYE value for London’s net international migration was more than 18% higher than 2022, and represents a considerable increase from 78,000 in 2021.

https://cdn.datapress.cloud/london/img/dataset/763802e7-af17-4b77-995d-44c494fb68af/2025-06-09T20%3A56%3A29/cb537d44954e11f7f7b7e2189ae74629.webp" width="1152" alt="Embedded Image" />

Age structure of the population

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Future Updates

The release of the next mid-year estimates is expected in July 2025.

The full ONS mid-year population estimates release and back series can be found on the ONS website: https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates.

For information relating to London’s population see the demography pages of the London Datastore: https://data.london.gov.uk/demography/ or email demography@london.gov.uk.

An in-depth review of the available evidence for population change in London since the start of the coronavirus pandemic has been produced by GLA Demography: https://data.london.gov.uk/dataset/population-change-in-london-during-the-pandemic.

National and subnational mid-year population estimates for the UK and its constituent countries by administrative area, age and sex (including components of population change, median age and population density).

The trend-based projections include a range of variants based on different assumptions about future levels of migration. The projections are produced for all local authorities in England & Wales and nationally for Scotland and Northern Ireland. The datasets include summary workbooks for London boroughs and detailed component of change outputs for all model areas.

The most recent set of trend-based population projections currently available are the 2020-based variant projections (September 2021).

The 2020-based projections comprise 4 principal variants which have been produced using different assumptions about future levels of domestic and international migration. Variant projections have been produced in order to assist users in understanding current uncertainty about future population growth. A full explanation of the differences between these projections is available in the supporting documentation.

Additionally, the trend-based projections also project the future number of households at local authority level by converting the projected population into households. Different sets of trend-based Household projections have been created using both the 2014-based DCLG household projection model and the 2018-based ONS household model so that users can compare the results of using these two different methodologies.

• Documentation page
• Back to projections homepage

The population of London reached over **** million in 2024, an increase of almost *** million people when compared with the early 1980s. Throughout the 1980s, the population of the United Kingdom's capital grew at a relatively slow rate, before accelerating to a much faster rate in the 1990s. London is by far the largest city / urban agglomeration in the United Kingdom, more than three times larger than the next largest cities of Manchester and Birmingham. London’s forecasted population is expected to continue growing at much the same pace it has been growing since the mid-1990s and reach almost *** million by 2042. London boroughs As of 2024, the London borough with the highest population was Croydon, at approximately *******, followed by Barnet at *******. Overall, London is divided into 33 different boroughs, with London's historic center, the City of London, having by far the smallest population, at just ******. Residents of the City of London, however, have the highest average median weekly earnings among all of London's boroughs, at ***** pounds per week, compared with just *** pounds per week in Redbridge, the lowest average weekly earnings among London boroughs. While the overall unemployment rate for London was 5** percent in early 2025, this ranged from ****percent in Newham, to just *** percent in Richmond upon Thames.
Economic imbalance Aside from being the UK's largest city in terms of population, London is also undoubtedly the UK's cultural, political and economic center. As of 2023, the GDP of Greater London was approximately *** billion British pounds, almost a quarter of the UK's overall GDP. In the same year, GDP per person in London was ****** pounds compared with the UK average of ****** pounds. Additionally, productivity in London is far higher than the UK average. As measured by output per hour worked, London was **** percent more productive than the rest of the UK.

Mid-year (30 June) estimates of the usual resident population for electoral wards in England and Wales. Note: this page is no longer updated. Latest estimates, and all data for mid-2012 onwards, are available on the Nomis website.

This is NOT a raw population dataset. We use our proprietary stack to combine detailed 'WorldPop' UN-adjusted, sex and age structured population data with a spatiotemporal OD matrix.

The result is a dataset where each record indicates how many people can be reached in a fixed timeframe (1 hour in this case) from that record's location.

The dataset is broken down into sex and age bands at 5 year intervals, e.g - male 25-29 (m_25) and also contains a set of features detailing the representative percentage of the total that the count represents.

The dataset provides 48420 records, one for each sampled location. These are labelled with a h3 index at resolution 7 - this allows easy plotting and filtering in Kepler.gl / Deck.gl / Mapbox, or easy conversion to a centroid (lat/lng) or the representative geometry of the hexagonal cell for integration with your geospatial applications and analyses.

A h3 resolution of 7, is a hexagonal cell area equivalent to: - ~1.9928 sq miles - ~5.1613 sq km

Higher resolutions or alternate geographies are available on request.

More information on the h3 system is available here: https://eng.uber.com/h3/

WorldPop data provides for a population count using a grid of 1 arc second intervals and is available for every geography.

More information on the WorldPop data is available here: https://www.worldpop.org/

One of the main use cases historically has been in prospecting for site selection, comparative analysis and network validation by asset investors and logistics companies. The data structure makes it very simple to filter out areas which do not meet requirements such as: - being able to access 70% of the UK population within 4 hours by Truck and show only the areas which do exhibit this characteristic.

Clients often combine different datasets either for different timeframes of interest, or to understand different populations, such as that of the unemployed, or those with particular qualifications within areas reachable as a commute.

Mid-year (30 June) estimates of the usual resident population for Lower layer Super Output Areas (LSOAs) in England and Wales by single year of age and sex.

In 2024, Croydon had the largest population among London boroughs at just over 409,340, followed by Barnet at 405,050.

UK residents by individual countries of birth and citizenship, broken down by UK country, local authority, unitary authority, metropolitan and London boroughs, and counties. Estimates from the Annual Population Survey.

Update 29-04-2020: The data is now split into two files based on the variable collection frequency (monthly and yearly). Additional variables added: area size in hectares, number of jobs in the area, number of people living in the area.

Context

I have been inspired by Xavier and his work on Barcelona to explore the city of London! 🇬🇧 💂

Content

The datasets is primarily centered around the housing market of London. However, it contains a lot of additional relevant data: - Monthly average house prices - Yearly number of houses - Yearly number of houses sold - Yearly percentage of households that recycle - Yearly life satisfaction - Yearly median salary of the residents of the area - Yearly mean salary of the residents of the area - Monthly number of crimes committed - Yearly number of jobs - Yearly number of people living in the area - Area size in hectares

The data is split by areas of London called boroughs (a flag exists to identify these), but some of the variables have other geographical UK regions for reference (like England, North East, etc.). There have been no changes made to the data except for melting it into a long format from the original tables.

Acknowledgements

The data has been extracted from London Datastore. It is released under UK Open Government License v2 and v3. The underlining datasets can be found here: https://data.london.gov.uk/dataset/uk-house-price-index https://data.london.gov.uk/dataset/number-and-density-of-dwellings-by-borough https://data.london.gov.uk/dataset/subjective-personal-well-being-borough https://data.london.gov.uk/dataset/household-waste-recycling-rates-borough https://data.london.gov.uk/dataset/earnings-place-residence-borough https://data.london.gov.uk/dataset/recorded_crime_summary https://data.london.gov.uk/dataset/jobs-and-job-density-borough https://data.london.gov.uk/dataset/ons-mid-year-population-estimates-custom-age-tables

Cover photo by Frans Ruiter from Unsplash

Inspiration

The dataset lends itself for extensive exploratory data analysis. It could also be a great supervised learning regression problem to predict house price changes of different boroughs over time.

Barnet is in the process of developing a transport strategy to understand and improve the way individuals travel across the borough. With population expected to reach 400,000 by 2020 Barnet is now London’s most populous borough. The growth in Barnet’s population will change our existing communities, attracting a younger and more diverse population, in addition to this, the increase in population will have a significant impact on the way people travel, which is why Barnet is planning to implement a strategy to manage this and make journeys for these people easier. The strategy will outline the Council’s commitment to improving transport options for all of our residents. This will involve considering what our appropriate “mix” of future travel modes should be and how we should be investing in various travel modes in order to arrive at a comprehensive choice of travel options for residents that effectively integrate with one another. It will also provide a high level blueprint to move forward and meet new and emerging challenges as well as providing a local application of the Mayor’s Transport Strategy goals. As part of this strategy an online library has been developed to provide a resource to reinforce decision making and make the strategy more transparent to stake holders. Barnet is in the process of developing a transport strategy to understand and improve the way individuals travel across the borough. With population expected to reach 400,000 by 2020 Barnet is now London’s most populous borough. The growth in Barnet’s population will change our existing communities, attracting a younger and more diverse population, in addition to this, the increase in population will have a significant impact on the way people travel, which is why Barnet is planning to implement a strategy to manage this and make journeys for these people easier. The strategy will outline the Council’s commitment to improving transport options for all of our residents. This will involve considering what our appropriate “mix” of future travel modes should be and how we should be investing in various travel modes in order to arrive at a comprehensive choice of travel options for residents that effectively integrate with one another. It will also provide a high level blueprint to move forward and meet new and emerging challenges as well as providing a local application of the Mayor’s Transport Strategy goals. As part of this strategy an online library has been developed to provide a resource to reinforce decision making and make the strategy more transparent to stake holders.

Comprehensive demographic dataset for London, TX, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

This mapping tool enables you to see how COVID-19 deaths in your area may relate to factors in the local population, which research has shown are associated with COVID-19 mortality. It maps COVID-19 deaths rates for small areas of London (known as MSOAs) and enables you to compare these to a number of other factors including the Index of Multiple Deprivation, the age and ethnicity of the local population, extent of pre-existing health conditions in the local population, and occupational data. Research has shown that the mortality risk from COVID-19 is higher for people of older age groups, for men, for people with pre-existing health conditions, and for people from BAME backgrounds. London boroughs had some of the highest mortality rates from COVID-19 based on data to April 17th 2020, based on data from the Office for National Statistics (ONS). Analysis from the ONS has also shown how mortality is also related to socio-economic issues such as occupations classified ‘at risk’ and area deprivation. There is much about COVID-19-related mortality that is still not fully understood, including the intersection between the different factors e.g. relationship between BAME groups and occupation. On their own, none of these individual factors correlate strongly with deaths for these small areas. This is most likely because the most relevant factors will vary from area to area. In some cases it may relate to the age of the population, in others it may relate to the prevalence of underlying health conditions, area deprivation or the proportion of the population working in ‘at risk occupations’, and in some cases a combination of these or none of them. Further descriptive analysis of the factors in this tool can be found here: https://data.london.gov.uk/dataset/covid-19--socio-economic-risk-factors-briefing

About this dataset

Context

The dataset tabulates the New London County population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of New London County across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2021, the population of New London County was 268,805, a 0.21% increase year-by-year from 2020. Previously, in 2020, New London County population was 268,248, an increase of 0.93% compared to a population of 265,784 in 2019. Over the last 20 plus years, between 2000 and 2021, population of New London County increased by 9,094. In this period, the peak population was 274,173 in the year 2012. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

https://i.neilsberg.com/ch/population-of-new-london-county-ct-population-by-year-2000-2021.jpeg" alt="New London County population by year">

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2021

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2021)
• Population: The population for the specific year for the New London County is shown in this column.
• Year on Year Change: This column displays the change in New London County population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New London County Population by Year. You can refer the same here

Introduction to fertility estimates

Fertility refers to the number of live births within an individual or group, influenced by a combination of biological, social, cultural, and economic factors.

There are several ways to describe fertility rates, but two of the most commonly used are Age-Specific Fertility Rates (ASFR) and Total Fertility Rates (TFR).

Age-specific fertility rates (ASFR) measure the number of births per woman within specific age groups. For example, in England, the peak childbearing age is currently 32, with an ASFR of 0.107, meaning 107 babies were born for each 1,000 women aged 32.

Total fertility rate (TFR) is a commonly used measure of overall fertility calculated as the sum of all age-specific fertility rates across all reproductive age groups. It represents the average number of children that a woman would have if she were to experience current age-specific fertility rates over the course of her life. For 2023, we estimate the TFR in Inner London to have been 1.16 compared to 1.54 in Outer London, and 1.41 for England as whole.

About these estimates

The estimates published here were produced by the GLA for use in analysis and as inputs to population projections. These data include annual estimates for all local authority districts and regions in England and Wales from 1993 onward of:

• Total Fertility Rates
• Age-Specific Fertility Rates by single year of age (15 to 49)

The GLA is making these estimates and the code used to create them as a resource for analysts and researchers working to understand local birth trends. We welcome feedback and suggestions from the community for how these data could be improved or made more useful.

The code used to produce these estimates is available on GitHub. All the requirements and information necessary to recreate the estimates can be found in the README file. This repository also includes some examples of code for plotting age-specific and total fertility rates across local authorities and periods of interest.

The Office for National Statistics also publishes fertility rates for local authority districts and higher geographies. Age-specific fertility rates are published by five-year age groups and for 2013 onward. These data are available to download from Nomis.

Note: There will be differences between the rates published by the GLA and those available from ONS. These are because the GLA:

• models rates for individual ages 15 to 19 and 40 to 49 from aggregate data
• applies smoothing to age specific rates
• uses population denominators for 2002 to 2020 that differ from the official mid-year estimates used by ONS.

Data and methods

The data used to calculate fertility rate estimates are:

• ONS calendar year births by age of mother from 1993
• ONS mid-year population estimates from 1991 - 2000
• GLA estimates components of change modelled backseries from 2000

Raw age-specific fertility rates are calculated by dividing the number of births in a calendar year by the population of women the same age at the mid-point of that year.

Smoothed rates, covering individual ages from 15 to 49 are produced by fitting a series of parametric curves to the raw fertility rates.

Age-specific fertility rates are summed across all ages to obtain total fertility rates.

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Annual population estimates as of July 1st, by census metropolitan area and census agglomeration, single year of age, five-year age group and gender, based on the Standard Geographical Classification (SGC) 2021.

These documents were produced through a collaboration between GLA, PHE London and Association of Directors of Public Health London. The wider impacts slide set pulls together a series of rapid evidence reviews and consultation conversations with key London stakeholders. The evidence reviews and stakeholder consultations were undertaken to explore the wider impacts of the pandemic on Londoners and the considerations for recovery within the context of improving population health outcomes. The information presented in the wider impact slides represents the emerging evidence available at the time of conducting the work (May-August 2020). The resource is not routinely updated and therefore further evidence reviews to identify more recent research and evidence should be considered alongside this resource. It is useful to look at this in conjunction with the ‘People and places in London most vulnerable to COVID-19 and its social and economic consequences’ report commissioned as part of this work programme and produced by the New Policy Institute. Additional work was also undertaken on the housing issues and priorities during COVID. A short report and examples of good practice are provided here. These reports are intended as a resource to support stakeholders in planning during the transition and recovery phase. However, they are also relevant to policy and decision-making as part of the ongoing response. The GLA have also commissioned the University of Manchester to undertake a rapid evidence review on inequalities in relation to COVID-19 and their effects on London.